00847nam0-2200265 --450 991059419570332120221003201459.020221003d1937----kmuy0itay5050 bafreFR 001yy<<L' >>organisation judiciaire, la procedure et la sentence internationalestraite pratiquepar J. C. Witenbergen collaboration avec Jacques DesriouxParisPedone1937VI, 436 p.26 cm34Witenberg,J.-C.1258593Desrioux,JacquesITUNINAREICATUNIMARCBK9910594195703321X E 3322820FGBCX E 3222836FGBCFGBCOrganisation judiciaire, la procedure et la sentence internationales2916614UNINA01991nam 2200409z- 450 991034705540332120231214132845.01000037914(CKB)4920000000101962(oapen)https://directory.doabooks.org/handle/20.500.12854/50472(EXLCZ)99492000000010196220202102d2014 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierInterdependence of Physical (In-) Activity, Fitness and Cognition: A Cross-Sectional Study in Young AdultsKIT Scientific Publishing20141 electronic resource (IV, 273 p. p.)Karlsruher sportwissenschaftliche Beiträge / Institut für Sport und Sportwissenschaft, Karlsruher Institut für Technologie (KIT). Hrsg.: Prof. Dr. Klaus Bös, PD Dr. Michaela Knoll3-7315-0164-3 There is growing evidence for possible associations between physical exercise, fitness and cognitive performance in elderly, but research in young adults is lacking. The aim of this cross-sectional study was to investigate the interdependence between physical (in-) activity, fitness, and cognition in young adults. The methods included a number of physical performance tests, a physical activity questionnaire, and a test battery to measure executive functions and event-related brain potentials.Interdependence of Physical KognitionSportExekutive FunktionenPhysical ActivityKörperliche AktivitätCognitionFitnessSportsExecutive FunctionsKrell-Rösch Janinaauth1325220BOOK9910347055403321Interdependence of Physical (In-) Activity, Fitness and Cognition: A Cross-Sectional Study in Young Adults3036700UNINA04406nam 2201201z- 450 991055764580332120220111(CKB)5400000000044995(oapen)https://directory.doabooks.org/handle/20.500.12854/76890(oapen)doab76890(EXLCZ)99540000000004499520202201d2021 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierEnergy Data Analytics for Smart Meter DataBasel, SwitzerlandMDPI - Multidisciplinary Digital Publishing Institute20211 online resource (346 p.)3-0365-2016-3 3-0365-2017-1 The principal advantage of smart electricity meters is their ability to transfer digitized electricity consumption data to remote processing systems. The data collected by these devices make the realization of many novel use cases possible, providing benefits to electricity providers and customers alike. This book includes 14 research articles that explore and exploit the information content of smart meter data, and provides insights into the realization of new digital solutions and services that support the transition towards a sustainable energy system. This volume has been edited by Andreas Reinhardt, head of the Energy Informatics research group at Technische Universität Clausthal, Germany, and Lucas Pereira, research fellow at Técnico Lisboa, Portugal.Technology: general issuesbicsscactivation currentambient influencesappliance load signaturesappliance recognitionattention mechanismconvolutional neural networkConvolutional Neural Networkdata annotationdata privacydata-driven approachesdeep learningdeep neural networkdeep neural networksdevice classification accuracydistance similarity matrixelectric load simulationelectric vehicleelectrical energyelectricity theft detectionenergy consumptionenergy data analyticsenergy data processingenergy disaggregationethicsexponential distributionfryze power theoryGaussian mixture modelsGDPRK-means clusterload disaggregationload schedulingmachine learningmathematical modelingmulti-label learningn/aNILMNILM datasetsnon-intrusive load monitoringNon-intrusive Load MonitoringNon-Intrusive Load Monitoring (NILM)nontechnical lossesPoisson distributionpower consumption datapower signaturepulse generatorrandom forestreal-timereviewsatisfactionsemi-automatic labelingShapley Valuesignaturesimulationsmart energy systemsmart gridsmart gridssmart metersmart meter datasmart meteringsmart meterssmart power gridssolar photovoltaicssynthetic datasynthetic minority oversampling techniquetext convolutional neural networks (TextCNN)time-series classificationtransient load signaturetransientsuser-centric applications of energy dataV-I trajectoryTechnology: general issuesReinhardt Andreasedt1295460Pereira LucasedtReinhardt AndreasothPereira LucasothBOOK9910557645803321Energy Data Analytics for Smart Meter Data3023469UNINA